Efficient Non-Malleable Commitment Schemes

Non-malleability protects against man-in-the middle attacks on cryptographic protocols. Non-malleable commitment schemes, for example, assure that a commitment of a message does not help to produce a commitment of a related message. Here we present efficient constructions of such commitment schemes in the common reference string model based on standard assumptions such as RSA, factoring, or discrete logarithm. Our protocols require only three rounds and a few modular exponentiations, and provide statistical or even perfect secrecy of committed values.     

Secure and Efficient Proxy Signature Scheme in the Standard Model

Existing proxy signature schemes are not proved to have complete security in the provable security model for proxy signature＇s whether the schemes are secure needs to be further studied. We show a generalized prov- able security model for proxy signature. Comparing with Boldyreva＇s security model, we introduce Schuldt＇s work to our security model. We propose a secure proxy signa- ture scheme, which is based on Waters＇ signature scheme in the standard model. Comparing with other proxy signa- ture schemes having a reduction to CDH assumption in the standard model, our scheme is more secure and efficient.     

可有效同步注册的短的群签名方案(英文)

Group signature schemes are fundamental cryptographic tools. A group signature scheme allows members of a group to anonymously sign misuse, the anonymity messages. To counter can be revoked by the group manager. The group joining operation is a critical component of group signature scheme, the framing attack can be prevented by group joining processes. This paper presents an efficient group signature scheme with a simple joining protocol that is based on a ＂single message and signature response＂ interaction between the prospective user and the group manager. The security of our group signature is based on the Discrete Logarithm assumption and Decisional Linear Diffie- Hellman assumption. The formal security proof of our scheme is given in the random oracle model. Our scheme is also a very efficient short group signature scheme with efficient concurrent join.     

A Learning Method for Pedestrian Activity Classification

Analysis of human activity and online anomaly detection from video sequences is one of the hottest and difficult research areas in computer visions. This paper describes a method for pedestrian gait classifi- cation in video sequence and deals with the classification of human gait types based on the notion that gait types can be analyzed into a series of consecutive postures types. First, silhouettes are extracted using the Background subtraction method which is combined with the time-stepping method. Then a method using recursion method for establishment of the standard gait state sequence is proposed. Mean- while, wavelet moment method is used to extract features of the human body image, and the result matrix leads to Discrete hidden Markov models. Finally, Discrete hidden Markov models is used for human posture training, model- ing and activity matching to recognize the human activity. The experiment tests show some encouraging results also indicates the algorithm has very small leak-examining and mistake-examining-rate, also shows the capability of real- time performance, which indicate that the method could be a choice for solving the problem but more tests are re- quired.     

Metabolic P Systems： A Discrete Model for Biological Dynamics

A recent methodology to model biochem- ical systems is here presented. It is based on a concep- tual framework rooted in membrane computing and de- veloped with concepts typical of discrete dynamical sys- tems. According to our approach, from data observed at suitable macroscopic temporal scales, one can deduce, by means of algebraic and algorithmic procedures, a dis- crete model （called Metabolic P system） which accounts for the experimental data, and opens the possibility to under- stand the systemic logic of the investigated phenomenon. The procedures of such a method have been implemented within a computational platform, a Java software called MetaPlab, processing data and simulating behaviors of metabolic models. In the paper, we briefly describe the theory underlying the modeling of biochemical systems by Metabolic P systems, along with its development stages and the related extensive literature.     

Distributed Compressive Video Sensing with Adaptive Measurements Based on Structural Similarity

This paper presents a Distributed compressive video sensing scheme with Adaptive measurements （DCVS-AM）. In this approach, the key frame in each Group of pictures （GOP） is coded by Compressive sensing （CS） with a fixed measurement rate; whereas other frames in the same GOP are compressed by an adaptive random projection in two stages, yielding the Adaptive compressive sensing （ACS） frames. The first stage uses a small and fixed measurement rate and recovers a coarse version. In the second stage, each coarse-version ACS-frame together with its proceeding and following key frames will go through a joint analysis at the decoder side and the analysis result - Structural similarity （SSIM） that is based on a motion-guided interpolation and calculated in a multilevel discrete wavelet transform domain - is sent back to the encoder side to facilitate a re-sampling of the ACS-frame with an adaptive measurement rate. Experimental results show that our proposed DCVS-AM consistently outperforms the state-of-the-art DCVS with a fixed measurement.     

Efficient Non-malleable Commitment Schemes

Non-malleability protects against man-in-the middle attacks on cryptographic protocols. Non-malleable commitment schemes, for example, assure that a commitment of a message does not help to produce a commitment of a related message. Here we present efficient constructions of such commitment schemes in the common reference string model, based on standard assumptions such as RSA, factoring or discrete logarithm. Our protocols require only three rounds and a few modular exponentiations, and provide statistical or even perfect secrecy of committed values. We also discuss differences between the notion of non-malleable commitment schemes used in previous works by Dolev, Dwork and Naor and by Di Crescenzo, Ishai and Ostrovsky. The former definition requires that it is infeasible to find a commitment such that there exists an encapsulated message which is related to another committed value (non-malleability with respect to commitment). The second approach allows the existence of such messages, but then it is hard to find them and to output them in the opening phase (non-malleability with respect to opening). We note that our solutions are of the second type.     

一种高效的动态群签名方案

在群签名系统中如何有效删除成员是一个重要的研究课题,王尚平提出的成员删除方案虽然高效,但已被证明不能达到真正删除成员的目的。新方案基于王尚平等人的群签名成员删除方案原理,利用中国剩余定理对不同合法成员的特性密钥更新算子进行不同的加密处理,从而达到真正删除成员的目的。基于强RSA假设和大整数分解的困难性,新方案具有较高的安全性。     

带有基于RSA签名的接入控制的不经意传输协议

该文在RSA签名及关于数据串的不经意传输的基础上提出了一种增强的不经意传输协议,解决了一种不经意传输的接入控制问题。除了具备一般不经意传输协议的特征外,该方案具有如下特点:只有持有权威机构发放的签字的接收者才能打开密文而且发送者不能确定接收者是否持有签字,即不能确定接受者的身份。在DDH假设和随机预言模型下该方案具有可证明的安全性。该方案使用标准RSA签名及Elgamal加密。     

一种匿名可撤销的比特币混淆方案

为解决用户在混币过程中无法请求退出的问题,该文提出一种支持用户匿名撤销混币的方案。采用承诺技术将用户和其目的地址进行绑定;当用户请求退出混洗服务时,利用累加器和知识签名对承诺进行零知识证明。最后将撤销用户的混淆输出地址修改为其指定的目的地址。安全性分析表明,该方案基于双离散对数问题和强RSA假设满足退群用户匿名性,且不用修改当前比特币系统即可实施。在n(n≥10)个诚实用户参与的混淆过程中,方案允许至多n–2个用户退出混币操作。     

基于广义XTR体制的签名方案

与RSA和ECC相比较,同等安全程度下XTR密钥长度远远小于RSA,最多只是ECC密钥长度的2倍;而XTR参数和密钥选取远远快于ECC。该文利用有限域中元素迹的快速算法,给出了两种特殊的基于广义XTR体制的签名方案,其安全性等价于解广义XTR群中的离散对数困难问题,但是传输的数据量只有原来方案的1/3.     

基于RSA算法的扩展算法

RSA的安全性是依据大整数分解的困难性而设计的。RSA公开密钥加密体制中n为2个大素数的乘积,即针对n=pq（p,q为大素数）的大整数分解,这里介绍了RSA算法的扩展算法的加密和解密原理,即针对n=p1,p2,…,pr（p1,p2,…,pr为大素数）的大整数分解。通过扩展素因子的个数达到RSA算法的安全性。比较RSA算法,扩展的RSA算法不仅可用于数据加密解密,也可用于数字签名。利用扩展的RSA算法实现数字签名也具有较高的安全性和可靠性。     

基于XTR体制的盲签名方案

XTR是一种新的基于有限域的乘法群的子群中元素迹的紧致表示的公钥密码体制。与RSA和ECC相比较,同等安全程度下 XTR密钥长度远远小于 RSA,最多只是 ECC密钥长度的 2倍,但XTR参数和密钥选取的速度远远快于 ECC。利用基于离散对数问题的盲签名方案以及有限域中元素迹的快速算法,该文给出了两种基于 XTR体制的盲签名方案,其安全性等价于解 XTR-DL困难问题,但是传输的数据量只有原来方案的 1/3。     

Self-Organization Approaches for Optimization in Cognitive Radio Networks

Cognitive radio （CR） is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques. However, cognitive radio networks （CRNs） may also impose some challenges due to the ever increasing complexity of network architecture, the increasing complexity with configuration and management of large-scale networks, fluctuating nature of the available spectrum, diverse Quality-of-Service （QoS） requirements of various applications, and the intensifying difficulties of centralized control, etc. Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm. In this paper, fundamentals of CR, including spectrum sensing, spectrum management, spectrum mobility and spectrum sharing, have been surveyed, with their paradigms of self-organization being emphasized. Variant aspects of self- organization paradigms in CRNs, including critical functionalities of Media Access Control （MAC）- and network-layer operations, are surveyed and compared. Furthermore, new directions and open problems in CRNs are also identified in this survey.     

A Probability Driven Quadri-Stage Contention Protocol for Mobile Ad Hoc Networks

The paper proposes a new contention based Time division multiple access （TDMA） Medium access control （MAC） protocol in wireless ad hoc networks, which can be termed Quadri-stage contention protocol （QSCP）. The QSCP protocol is free of both the ＂hidden terminal＂ and the ＂exposed terminal＂ problems. It is distributive and arbitrarily scalable. In the dedicated contention stage, nodes exchange their ＂Normalized accumulation and dissipation rate of payload （NADROP）＂ messages in 2-hop neighborhood, and then run a contention probability calculation algorithm to decide the probability of sending a contention frame. The algorithm guaran- tees that the number of time slot reserved by a node is proportional to its NADROP value, which can remarkably improve the end-to-end throughput when network load is heavy, and is more efficient in energy consumption. The simulation results demonstrate that QSCP performs better than the existing protocols.     

Best Effort Spectrum Allocation Scheme for Femtocell Networks in Dense Deployment

In orthogonal frequency division multiple access（OFDMA） based femtocell networks,the co-tier interference among femto base stations（FBS） becomes important in multiuser and densely deployed environment.In order to mitigate the co-tier interference and enhance the system total throughput,this paper proposed a best effort spectrum allocation scheme based on the extension of graph theory.In the scheme,a controller was proposed to collect the channel state information（CSI）of all femtocell user equipments（FUEs） in a certain range.Then,the controller evaluated the signal-to-interference Ratio（SIR） of each FUE and determined the set of its interference neighbors.By calculating the received power matrix（RPM） among FUEs and building interference graph matrix（IGM）,different spectrum resource blocks（RBs） were assigned to the users with interference relation,while users without interference relation shared the same RBs,which could increase the spectrum efficiency.Simulation results show that the proposed algorithm can significantly improve the RB usage efficiency compared with the basic graph coloring theory,and more than 80% improvement can be acquired in dense deployment scenario.Besides,the throughput of both cell edge macro user equipments（MUEs） and cell edge FUEs is guaranteed on the premise of low interference.     

A Fuzzy Similarity-based Clustering Optimized by Particle Swarm Optimization

Traditional fuzzy clustering algorithms based on objective function is unable to determine the optimum number of clusters, sensitive to the initial cluster centers, and easily sunk into the issue of local optimum. A Fuzzy similarity-based clustering （FSBC） algorithm is proposed in this paper. This method consists three phases： first, the objective function is modified by integrating Fuzzy C-means （FCM） and Possibilistic C-means （PCM） method; second, using the density function from data for similarity-based clustering to automatically generate initial prototype without requesting users to specify; finally, the iteration process optimized by Particle swarm optimization （PSO） to obtain appropriate adjustment parameters that can provide better results, which avoids the local minimum problems of traditional methods. The experimental results on the synthetic data and UCI standard data sets show that the proposed algorithm has greater searching capability, less computational complexity, higher clustering precision.     

A Scalable Peer-to-Peer Web Services Overlay for Semantic Discovery

The growing number of web services advocates distributed discovery infrastructures which are semantics-enabled. We introduce a novel approach for semantic discovery of web services in structured P2P-based （Peer-to-Peer） registries. We partition concepts into different CGs （Concept groups） and index these ordered concept sets in a two-phase semantic routing mechanism. Each node and query has one concept set as its unique ID. For each concept in the query, current node first route the query to a node with nodeID that shares a prefix as long as with the query, but a longer CG. Second, the query will be routed to a node sharing a longer prefix than that of the current node. Combining with semantic similarity calculation, our proposal guarantees that most existing services matching a query will be found with bounded costs in terms of number of nodes involved. The scalability and reliability of our approach are also confirmed through emulation tests.     

Action-Based Access Control Modelt

Access control is one of the powerful and generalized approaches for restricted resource access. The environmental state is introduced and the term “action” is defined based on roles, temporal states and environmental states. Actions can be used to capture security-relevant aspects of roles, environmental and temporal states in different information systems. Then, the action hierarchy, environmental hierarchy, temporal hierarchy and Action- based access control （ABAC） model are presented. ABAC is compared with the existing models and the result shows that the ABAC model can solve the problem of access control in information systems with mobile computation for its convenient and flexible designs. An application example of ABAC model is described at the end of the paper.     

Novel Active Contour Model for Image Segmentation Based on Local Fuzzy Gaussian Distribution Fitting

A novel active contour model is proposed, which incorporates local information distributions in a fuzzy energy function to effectively deal with the intensity inhomogeneity. Moreover, the proposed model is convex with respect to the variable which is used for extracting the contour. This makes the model independent on the initial condition and suitable for an automatic segmentation. Furthermore, the energy function is minimized in a computationally efficient way by calculating the fuzzy energy alterations directly. Experiments are carried out to prove the performance of the proposed model over some existing methods. The obtained results confirm the efficiency of the method.